1. Migration of reconstruction and analysis software to C++
A proposal based on feedback from the software week
Marco Cattaneo, 1st December 1999

2. Immediate Goals Physics Goal: Software Goal
To be able to run new tracking pattern recognition algorithms written in C++ in production with standard FORTRAN algorithms in time to produce useful results for the RICH TDR.
Software Goal
To allow software developers to become familiar with GAUDI and to encourage the development of new software algorithms in C++.
Marco Cattaneo, 1st December 1999

3. Proposed Strategy - Step 1
Finish splitting of SICB into:
simulation (SICBMC)
Event generation, GEANT tracking
outputs kinematics AND raw GEANT hits
i.e. Current RAW format, but with xxRW banks from all detectors
reconstruction (SICBREC)
doesn’t need GEANT3 nor its common blocks
digitisation, trigger, reconstruction in distinct steps
outputs same DST format as now.
Benefits:
Clear separation between simulation and reconstruction
Modularity of reconstruction
Organiser : Florence
Marco Cattaneo, 1st December 1999

4. SICB “digitisings” (not on SICB DST)
Step 1 overview
SICBREC
SICBSIM
Generator
SICB local
tracking and
“digitisation”
Half way between raw data and coordinates. E.g. wire number, signed drift distance
MC Kinematics
Pileup
SICB “digitisings” (not on SICB DST)
GEANT
transport
Pattern
Recognition
Trigger
SICB “raw” data
Entrance and exit points and energy loss in detectors
SICB DST
Marco Cattaneo, 1st December 1999

5. Tasks for step 1 SICBMC SICBREC
Remove anything that belongs to digitisation and reconstruction
Done
Create raw hits for calorimeter
To be done by calorimeter experts (~1 week?)
SICBREC
Add initialization routines for each step of the processing (digitize, apply trigger, reconstruction)
Verify validity of results
Both the above are essentially work for the sub-detector experts
Time estimate is about two weeks
If started now, step 1 could be finished by Xmas
Marco Cattaneo, 1st December 1999

6. Step 1 SICBREC structureX
This dataflow is forbidden
(no COMMON...)
SICB raw
Digitisation A
Digitisation B
Trigger
Reconstruct A
Reconstruct B
Input
ZEBRA common (SICB banks)
Output
SICB “framework”
SICB DST
Marco Cattaneo, 1st December 1999

7. Proposed Strategy - Step 2
For every SICBREC FORTRAN module:
wrap it such that it can be called from C++
Integrate with the GAUDI framework
Time estimate about 1 month - sub-detectors and Gaudi team
Result is a new reconstruction program - BRUNEL
Produce a DST (Zebra banks) with this program
check the output is as expected
i.e. identical to SICBREC output
Must be done by sub-detector experts
Drop SICBREC
Could be ready for decision by next LHCb week
Benefit:
Single environment for C++ and FORTRAN work
Integrated environment for verification of C++ developments
Organiser: Marco

8. Step 2 BRUNEL structure SICB raw ZEBRA common (SICB banks)
Digitisation A
Digitisation B
Trigger
Reconstruct A
Reconstruct B
Input
ZEBRA common (SICB banks)
Output
Gaudi framework
SICB DST
Marco Cattaneo, 1st December 1999

9. Proposed Strategy - Step 3
Start replacing FORTRAN modules with C++ equivalent. Each new piece consists of:
event model
detector description
algorithm.
Provide converters to:
regenerate same SICB output bank that was there before
Preserves format of SICB DST
DST banks may contain improved data (e.g. Result of tracking pattern recognition
Some “added value” of C++ algorithms would NOT be on SICB DST
write data out to the supported persistent object manager
Contains as complete a reconstructed event as is available in GAUDI event store
Including “added value” of C++ algorithms, available only to GAUDI based analyses
Marco Cattaneo, 1st December 1999

10. Step 3 - organisation This step implies (for each sub-detector):
Development of event model : help coordinated by Marco
Development of detector description : help coordinated by Florence
Reviews of evt mod, det desc, algorithms : organised by John.
Review panel will include Pere, Marco, Florence, plus SDs
Known candidates:
Tracking,
Analysis tools,
Muon digitisation,
Calorimeters,
RICH,
...
Timescale:
Depends (almost) entirely on sub-detectors
Marco Cattaneo, 1st December 1999

11. Step 3 BRUNEL structure CDF files SICB raw SICB DST
Digitisation A
Digitisation B
Trigger
Reconstruct B
Zebra
Input
Zebra
Output
ZEBRA common (SICB banks)
Sicb
Converters
Sicb
Converter
Gaudi transient event store
Sicb
Converters
Reconstruct A
BRUNEL OO
Output
XML geom.
OO DST

12. Step 3: Analysis structure
SICB DST
Analysis A
Has access ONLY to SICB DST
Steered by GAUDI job options
GAUDI
Zebra
Input
ZEBRA common (SICB banks)
HBOOK
GAUDI job options
Sicb
Converters
Gaudi transient event store
Sicb
Converters OO
Input
Analysis B
Visualisation
Have access to OO DST and SICB
banks for which converters exist.
Steered by GAUDI job options
OO DST

13. Step 3 - benefits A unified development and production environment
As soon as C++ algorithms are proven to do the right thing, they can be brought into production in the official reconstruction program
Early exposure of all developers to Gaudi infrastructure
FORTRAN gurus and C++ beginners
Increasing functionality of OO ‘DST’
As more and more of the event data becomes available in Gaudi, it will become more and more attractive to perform analysis with Gaudi
N.B. Contains ALL (and only!) parts of reconstructed event for which data model is defined
A smooth transition to a C++ only reconstruction
Marco Cattaneo, 1st December 1999

14. Summary Step 1: separate SICBMC and SICBREC
Could be ready by Xmas
Step 2: wrap SICBREC algorithms into Gaudi framework
Could be ready by end February
Step 3: gradually replace FORTRAN with C++ algorithms
Timescale dictated by sub-detector priorities
Development/integration in Gaudi can start now
Analysis in Gaudi is possible now
Functionality will increase as subdetectors define their data model
Analysis toolkit under development, send requirements to Gloria
Marco Cattaneo, 1st December 1999